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과학적 실행에서의 데이터 모델링 탐색- 현상의 생성과 증거를 만드는 과정을 중심으로 -

Exploring Data Modeling in Scientific Practice - Focusing on Phenomenon Production and Evidencing -

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주제분류교육학

초록

The purpose of this case study is to examine the characteristics of data modeling in the scientific research conducted in the university laboratory. The artifacts during the two-year research, such as research plans, presentation materials in the lab seminar, and master's thesis, were used as the main sources and analyzed according to qualitative methods. The results of the study provide the characteristics of data modeling and the discussions its educational implications. First, data modeling gradually shows a complex and dynamic pattern in the relationship between the model of experiment and the theoretical model. Second, phenomena are produced, changed, and stabilized in the data modeling process. Third, through the data modeling, data models gradually acquire status as evidence. The results of the study provide new implications for science education by unfolding the characteristics of data modeling that have not been noticed in science education through scientific research in the laboratory.

Abstract

The purpose of this case study is to examine the characteristics of data modeling in the scientific research conducted in the university laboratory. The artifacts during the two-year research, such as research plans, presentation materials in the lab seminar, and master's thesis, were used as the main sources and analyzed according to qualitative methods. The results of the study provide the characteristics of data modeling and the discussions its educational implications. First, data modeling gradually shows a complex and dynamic pattern in the relationship between the model of experiment and the theoretical model. Second, phenomena are produced, changed, and stabilized in the data modeling process. Third, through the data modeling, data models gradually acquire status as evidence. The results of the study provide new implications for science education by unfolding the characteristics of data modeling that have not been noticed in science education through scientific research in the laboratory.

참고문헌 (49)

  1. Bae, D., "Middle school students’ learning progression for scientific modeling a force and motion phenomenon", Master, pp.2012
  2. Bailer-Jones, D. M., "Scientific Models in Philosophy of Science" (2009), University of Pittsburgh Press
  3. Bogen, J., "Saving the phenomena", The Philosophical Review, 97(3), pp.303~352 (1988)
  4. Chinn, C. A., "Epistemologically authentic inquiry in schools : A theoretical framework for evaluating inquiry tasks", Science Education, 86(2), pp.175~218 (2002)
  5. Creswell, J. W., "Qualitative Inquiry and Research Design Choosing among Five Approaches" (2018), SAGE Publications,Inc
  6. Flick, L. B., "Science Inquiry and Nature of Science Lmlpications for Teaching, Learning, and Teacher Education" (2006), Springer
  7. Garcia-Mila, M., "Argumentation in Science Education", pp.29~45 (2008), Springer
  8. Giere, R. N., "The Experi-mental Side of Modeling", pp.59~70 (2018), University of Minnesota Press
  9. Gilbert, J. K., "Models in explanations, Part 1 : Horses for courses?", International Journal of Science Education, 20(1), pp.83~97 (1998)
  10. Gilbert, J. K., "Developing Models in Science Education", pp.3~17 (2000), Kluwer Academic
  11. Gonsior, M., "Sli is required for proper morphology and migration of sensory neurons in the Drosophila PNS", Neural Development, 14(1), pp.1~11 (2019)
  12. Goodwin, C., "Co-Operative Action (Learning in Doing:Social, Cognitive, and Computational Perspectives)" (2017), Cambridge University Press
  13. Grandy, R., "Reconsidering the character and role of inquiry in school science : Analysis of a conference", Science & Education, 16, pp.141~166 (2007)
  14. Halloun, I. A., "Modeling Theory in Science Education" (2006), Springer
  15. Hardahl, L. K., "The body and the production of phenomena in the science laboratory : Taking charge of a tacit science content", Science & Education, 28(8), pp.865~895 (2019)
  16. 한미영, "데이터 기반 과학 탐구 사례 연구", 현장과학교육, 16(2), pp.165~178 (2022), 한국현장과학교육학회[DOI]
  17. Huh, J., "Experimental lesson development for improving pre-service teachers’ scientific understanding of rainbow, halo corona", doctor, pp.2015
  18. Jimenez-Aleixandre, M. P., "Argumentation in Science Education: Perspectives from Classroom-Based Research", pp.3~27 (2008), Springer
  19. Jiménez-Aleixandre, M. P., "Determinism and underdetermination in genetics : Implication for students’engagement in argumentation and epistemic practice", Science & Education, 23(2), pp.465~484 (2014)
  20. Jo, Y. -H., "Qualitative description, analysis, interpretation", The Korean Society for The Study of Anthropology of Education, pp.27~63 (1999)
  21. 김희경, "학생의 논변활동을 강조한 개방적 과학탐구활동 모형의 탐색", 한국과학교육학회지, 24(6), pp.1216~1234 (2004), 한국과학교육학회
  22. 김관영, "학생의 자유 탐구 활동의 사례 분석을 통해 본 실험 모델링의 특징과 과학교육적 의미", 한국과학교육학회지, 42(2), pp.201~214 (2022), 한국과학교육학회
  23. Kuhn, D., "Handbook of Child Psychology: Vol. 2, Cognition, Perception, and Language", pp.953~993 (2006), Wiley
  24. 이차은, "과학적 모형 구성 과정에서 나타난 사고 질문의 개념적 자원 활성화의 이해 -인식론적 프레이밍과 위치 짓기 프레이밍을 중심으로-", 한국과학교육학회지, 36(3), pp.471~483 (2016), 한국과학교육학회[DOI]
  25. 이신영, "배설에 대한 협력적 모델링 과정에서 나타난 중학교 학생들의 대화적 논변활동 탐색", 한국과학교육학회지, 37(6), pp.1037~1049 (2017), 한국과학교육학회[DOI]
  26. 이선경, "고등학교 과학수업 사례 분석을 통한 학교 과학 탐구의 특징", 한국과학교육학회지, 33(2), pp.284~309 (2013), 한국과학교육학회
  27. 이선경, "프로젝트 기반 과학 활동 과정에서 나타나는 학생 탐구의 특징: 증거-이론-방법의 조정과 도구 사용의 솜씨를 중심으로", 한국과학교육학회지, 35(4), pp.599~608 (2015), 한국과학교육학회[DOI]
  28. Magnani, L., "Model-Based Reasoning: Science, Technology, Values", pp.2002, Kluwer Academic
  29. Magnani, L., "Model-based and manipulative abduction in science", Foundation of Science, 9, pp.219~247 (2004)
  30. McNeil, K. L., "Elementary students’ views of explanation, argumentation, and evidence and their abilities to construct arguments over the school year", Journal of Research in Science Teaching, 48(7), pp.793~823 (2011)
  31. Millar, R., "Practical Work in Science Education: Which Way Now?", pp.16~31 (1998), Routledge
  32. Ministry of Education, "The National Science Curriculum", Ministry of Education, ~ (2015)
  33. Moshman, D., "Handbook of Child Psychology: Vol. 2, Cognition, Perception, and Language", pp.947~978 (1998), Wiley
  34. National Research Council, "National Science Education Standards" (1996), National Academy Press
  35. NGSS Lead States, "Next Generation Science Education Standards: For States, by States" (2013), The National Academies Press
  36. Oh, P. S., "Features of modeling-based abductive reasoning as a disciplinary practice of inquiry in earth science", Science & Education, 28, pp.731~757 (2019)
  37. 오필석, "과학 교육에서 기능 중심의 과학 탐구에 대한 비판적 고찰", 한국과학교육학회지, 40(2), pp.141~150 (2020), 한국과학교육학회[DOI]
  38. Passmore, C., "Exploring opportunities for argumentation in modelling classrooms", International Journal of Science Education, 34(10), pp.1535~1554 (2012)
  39. Pierson, A. E., "Dimensions of co-operative action at a classroom scale", Science &Education, 28, pp.897~925 (2019)
  40. Pierson, A. E., "Learning progressions and science practices", Science &Education, 28(8), pp.833~841 (2019)
  41. Rea-Ramirez, M. A., "Model Based Learning and Instruction in Science", pp.23~43 (2008), Springer
  42. Roth, W. M., "Authentic School Science" (1995), Kluwer Academic Publisher
  43. 유금복, "행위자-네트워크 이론으로 본 과학적 실행의 현상 생성 사례", 교과교육학연구, 26(2), pp.179~190 (2022), 교과교육연구소[DOI]
  44. Sampson, V., "Argument-driven inquiry as a way to help students learn how to participate in scientific argumentation and craft written arguments : An exploratory study", Science Education, 95(2), pp.217~257 (2011)
  45. Schwarz, C. V., "Developing a learning progression for science modeling : Making scientific modeling accessible and meaningful for learners", Journal of Research in Science Teaching, 46(6), pp.632~654 (2009)
  46. 손미현, "지식정보처리역량 함양을 위한 데이터 기반 과학탐구 모형 개발", 한국과학교육학회지, 40(6), pp.657~670 (2020), 한국과학교육학회[DOI]
  47. 정대홍, "지식정보화 사회에서의 과학탐구 교육 방향성 탐색", 현장과학교육, 14(3), pp.401~414 (2020), 한국현장과학교육학회[DOI]
  48. von Hilchen, C. M., "Identity, origin, and migration of peripheral glial cells in the Drosophila embryo", Mechanisms of Development, 125(3-4), pp.337~352 (2008)
  49. Wolcott, H., "Transforming Qualitative Data: Description, Analysis, and Interpretation" (1994), Sage

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